Logging while drilling (LWD) techniques for determining numerous borehole and formation characteristics are well known in oil drilling and production applications. Such LWD techniques include, for example, natural gamma ray, spectral density, neutron density, inductive and galvanic resistivity, micro-resistivity, acoustic velocity, acoustic caliper, physical caliper, and the like. As is well known in the art, LWD has enabled the measurement of such borehole and formation parameters to be conducted during the drilling process. The measurement of borehole and formation properties during drilling has been shown to improve the timeliness and quality of the measurement data and to often increase the efficiency of drilling operations.
Borehole imaging has become conventional in logging while drilling applications. Such images provide an indication of the azimuthal sensitivity of various borehole and/or formation properties. LWD imaging applications commonly make use of the rotation (turning) of the bottom hole assembly (BHA) (and therefore the LWD sensors) during drilling of the borehole. For example, Holenka et al., in U.S. Pat. No. 5,473,158, discloses a method in which sensor data (e.g., neutron count rate) is grouped by quadrant about the circumference of the borehole. Likewise, Edwards et al., in U.S. Pat. No. 6,307,199, Kurkoski, in U.S. Pat. No. 6,584,837, and Spross, in U.S. Pat. No. 6,619,395, disclose similar methods. For example, Kurkoski discloses a method for obtaining a binned azimuthal density of the formation. In the disclosed method, gamma ray counts are grouped into azimuthal sectors (bins) typically covering 45 degrees in azimuth. Accordingly, a first sector may include data collected when the sensor is positioned at an azimuth in the range from about 0 to about 45 degrees, a second sector may include data collected when the sensor is positioned at an azimuth in the range from about 45 to about 90 degrees, and so on.
More recently, commonly assigned U.S. Pat. No. 7,027,926 to Haugland discloses a technique in which LWD sensor data is convolved with a one-dimensional window function. This approach advantageously provides for superior image resolution and noise rejection as compared to the previously described binning techniques. Commonly assigned, co-pending U.S. Patent Publication 2009/0030616 to Sugiura describes another image constructing technique in which sensor data is probabilistically distributed in either one or two dimensions (e.g., azimuth and/or measured depth). This approach also advantageously provides for superior image resolution and noise rejection as compared to prior art binning techniques. Moreover, it further conserves logging sensor data (i.e., the data is not over or under sampled during the probabilistic distribution) such that integration of the distributed data may also provide a non-azimuthally sensitive logging measurement.
One problem with conventional LWD imaging techniques is that the obtained images commonly include cyclical or oscillating noise. For example, a spiralling effect is commonly observed in borehole images. This effect may be caused by a spiralling (or helically shaped) borehole or by periodic oscillations in the borehole diameter. Such cyclic noise often complicates the interpretation of borehole image data, for example, the identification of various geological features and the quantitative determination of formation parameters, such as formation thickness, dip and dip azimuth etc. Therefore, there is a need in the art for improved borehole imaging techniques and in particular a method for removing and/or quantifying cyclical noise on borehole images.